This PDW addresses the critical need for sustainable teaching methods in the era of Generative AI. As Generative AI becomes integral to personal and professional domains, educators face the challenge of preparing learners for a rapidly evolving technological landscape. However, we cannot predict the competencies future generations will need. This uncertainty calls for a pedagogical shift: from content delivery and tool-specific training to fostering sustainable competencies such as critical inquiry, self-regulated learning, and creative problem-solving. Our workshop introduces Adaptive Resilience Pedagogy, a framework equipping learners with timeless skills to navigate the challenges and opportunities of Generative AI. Central to this approach and USP of our PDW is the "pedagogical double-decker" method, which teaches both method and content simultaneously. Learners engage AI tools as a means of learning (e.g., for data analysis, project collaboration) while critically reflecting on AI as a subject (e.g., algorithmic bias, ethics). This dual approach fosters deep understanding and adaptability, aligning with Resilient Learning principles. Through interactive discussions, hands-on activities, and collaborative exercises, we explore together with our participants practical applications of this method to enhance higher education. Our PDW is intended to foster intense exchange between peers. We introduce an innovative and flexible teaching model, and simultaneously empower educators to embrace Generative AI as a partner in building their future-ready education practices.
